Day #10 – Exploring Twitter Data
As part of my Power BI 12 Days of Dashboards series, day #10 explores Twitter data with four different interactive dashboards.
I’ve had a Twitter account for a few years, but have only started to use it regularly over the past 6-8 months. I presented at a conference in Copenhagen, Denmark, in May 2016 and started to see activity with followers, people tweeting messages regarding our presentation, etc. Since that time, I’ve started to use it on a regular basis, sharing blog entries, projects, and news. I’m still a very small fish in the Twitter pond, but I’ve really enjoyed the interactions and the data that it has generated.
Today’s entry showcases four different ways to explore your Twitter data and interactions (profile clicks, retweets, likes, etc.).
Microsoft Campaign/Brand Management for Twitter
The Power BI team has created several amazing solution templates, which are easy to deploy end-to-end solutions leveraging multiple data sources (SAP, Dynamics 365, Salesforce, and SCCM). My current favorite, called the Campaign/Brand Management for Twitter, is a visually beautiful series of reports that analyzes Twitter data to provide sentiment analysis, topic trending, top interactions, and much more.
I have deployed the solution below to track my Twitter handle (@SQLSamLester) as well as the hashtag I created for this dashboard series (#12DaysOfDashboards). The report is live, so feel free to tweet/retweet and include either my username or hashtag and see the interaction show up in the dashboard within a few minutes. There are six different report panes, so be sure to check out each of them.
Personalized Twitter Dashboard – When do I tweet the most? When do my tweets receive the most attention?
I published a blog entry earlier this year titled “Create your personalized Twitter Analytics Dashboard in Power BI in 10 minutes!“, showing how to use your exported Twitter stats as the data source in a Power BI template (much like the theme of this blog series). This leverages the built-in export capability from Twitter and can be easily extended depending on your interaction focus. The blog entry is very basic and walks you through creating your own Twitter dashboard in just a few minutes by including the pre-built Power BI Template. All you need to do is export your stats and change the data source in the template (detailed instructions included in the blog). Check out the Power BI Data Stories Gallery for additional dashboards.
Analysis of Twitter Followers by DataChant.com
I’ve really enjoyed the amazing work that DataChant (Gil Raviv) has been producing in Power BI around text analytics, key phrase extraction from Facebook messages, and sentiment analysis. Between the DataChant website and the guest blogs Gil writes for the Power BI Community Blog, there is a wealth of information for getting started with these areas.
Below is an example of the Twitter Follower Analysis Dashboard Gil created to help me analyze my followers. The word cloud visual that consists of key phrases from follower’s descriptions was very insightful. Prior to using this, I didn’t know of a nice way to determine who works at Microsoft and follows me on Twitter. I used the word cloud filter along with the map to locate other Microsoft employees that live in Europe and share similar interests in social media, Power BI, and contributing to the technical community.
In addition to the great work in Twitter data analysis, DataChant had also been busy providing Facebook data analysis as well. Thanks to DataChant for this great work and for the Twitter Dashboard for my followers.
Geographic Heat Map of Twitter Followers
I wasn’t able to export the country location of Twitter followers through built-in export functionality, so I leveraged a Twitter analytics site called TweepsMap to obtain this data. TweepsMap creates a very nice map and a few other visuals with your Twitter follower location, which you can use to post to Twitter on a regular basis, along with many other great analytics services. In this case, I just wanted access to the data to build the following heat map in Power BI using the filled map.
One of the primary goals of this blog series is to help people understand the power of data and the incredible ways in which you can leverage Power BI to view and analyze this data. I hope these different techniques help showcase the amazing power of Power BI. Have fun exploring your Twitter data and please share a comment if you come up with additional insights.
Sam Lester (MSFT)